The following estimated regression equation is based on 30 observations.ŷ 18+ 3.8x12.52 +7.73 +2.9x4The values of SST and SSR are 1,802 and 1,755, respectively.a. Compute R² (to 3 decimals).b. Compute R² (to 3 decimals).c. Comment on the goodness of fit.The estimated regression equation - Select your answer -

The estimated regression equation is 18+3.8x1-2.5x2+7.7x3+2.9x4As per given regression equation,…

Answered: The following estimated regression…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 2.3 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) Weight (kg) 7.8 175 7.3 9.5 274 7.4 156 9.9 294 9.2 183 256 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... The regression equation is y =+x. (Round to one decimal place as needed.)
Find the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 78.5Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.1 per 10 million people? Internet Users Per 100 Nobel Laureates80.3 5.679.6 24.277.3 8.644.6 0.183 6.138.3 0.190.1 25.189.1 7.680.1 8.983.3 12.753.2 1.976.6 12.756.8 3.379.5 1.591.5 11.493.7 25.465.1 3.157.8 1.967.9 1.794.3 31.785.3 31.387.7 1977.7 10.8
The data show the bug chirps per minute at different temperatures. Find the regression equation, letting the first variable be the independent (x) variable. Find the best-predicted temperature for a time when a bug is chirping at the rate of 3000chirps per minute. Use a significance level of 0.05. What is wrong with this predicted value? Chirps in 1 min 1004 952 1237 1116 1177 1249 Temperature (°F) 83.1 76 95.1 87.5 92.1 88.4 What is the regression equation? (^ over y)=_____+_____x (Round the x-coefficient to four decimal places as needed. Round the constant to two decimal places as needed.) What is the best-predicted temperature for a time when a bug is chirping at the rate of 3000chirps per minute? The best-predicted temperature when a bug is chirping at 3000 chirps per minute is ____°F. (Round to one decimal place as needed.) What is wrong with this predicted value? Choose the correct answer below. A. It is…
Find the regression equation, letting the diameter be the predictor (x) variable. Find the best predicted circumference of a marble with a diameter of 1.9 cm. How does the result compare to the actual circumference of 6.0 cm? Use a significance level of 0.05. Baseball Basketball Golf Soccer Tennis Ping-Pong Volleyball 5 Diameter 7.4 23.6 4.3 21.7 7.1 3.9 21.5 Circumference 23.2 74.1 13.5 68.2 22.3 12.3 67.5
2
Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the valuo of v for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y 762 621 508 480 (b) x = 641 feet (d) x = 726 feet 515 491 (a) x= 498 feet (c) x = 810 feet 51 46 44 42 38 37 Find the regression equation. ý=x+ (D (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. OA. OB O B. Oc. OD. 60- 604 60+ 800 B00 G 800 Height (feet) 800 Height (feet) 800 Height (feet) Height (feet) (a) Predict the value of y for x = 498. Choose the correct answer below. OA 40 ОВ. 50 O C. 47 O D. not meaningful (b) Predict the value of y for x 641. Choose the correct answer…
Find the regression equation, letting overhead width be the predictor (x) variable. Find the best predicted weight of a seal if the overhead width measured from a photograph is 2.5 cm. Can the prediction be correct? What is wrong with predicting the weight in this case? Use a significance level of 0.05. Overhead Width (cm) 7.6 7.4 9.8 8.8 9.3 7.3 Weight (kg) 142 163 256 188 231 156 The regression equation is y= + x. (Round to one decimal place as needed.) The best predicted weight for an overhead width of 2.5 cm is kg? (Round to one decimal place as needed.) Can the prediction be correct? What is wrong with predicting the weight in this case? A. The prediction cannot be correct because a negative weight does not make sense. The width in this case is beyond the scope of the available sample data. B. The prediction cannot be correct because a negative weight does not make sense and because there is…
An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:. Summary measures Multiple R 0.9689 R-Square 0.9387 Adj R-Square 0.9212 StErr of Estimate 72.218 Regression coefficients Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.
Which of the multivariate regression parameters listed below would be best interpreted as: the proportion of variation in the dependent variable explain by all the independent variables in the model. a b1 X1 R2
Use the shoe print lengths and heights shown below to find the regression equation, letting shoe print lengths be the predictor (x) variable. Then find the best predicted height of a male who has a shoe print length of 28.5 cm. Would the result be helpful to police crime scene investigators in trying to describe the male? Use a significance level of α=0.05. Shoe Print (cm) 29.1 29.1 31.8 31.9 27.5 Foot Length (cm) 25.7 25.4 27.9 26.7 25.1 Height (cm) 175.4 177.8 185.2 175.4 173.2 The best predicted height is enter your response here cm. (Round to two decimal places as needed.) Would the result be helpful? A. No, because the description would be the same regardless of shoe print length. B. Yes, because the description would be based on an actual shoe print length. C. Yes, because the correlation is strong, so the predicted…

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